1. Field of the Invention
The present invention relates to an image processing apparatus and method for determining, e.g., the quantization threshold of a multivalued image to perform quantization.
2. Description of the Related Art
The recent development of image processing techniques is remarkable, and image processing apparatuses capable of processing of a multivalued image such as a full-color image, and character recognition processing in the multivalued image are becoming popular. In these image processing techniques, binarization processing of a multivalued image is an indispensable technique.
In addition to a simple binarization method using a fixed threshold set in advance, conventional binarization methods include the Otsu's method (Otsu, "Automatic Threshold Selection Method Based on Discrimination and Least Square Rule", the transactions of the Institute of Electronics and Communication Engineers of Japan, Vol. J63-D, No. 4, pp. 349-356, 1980) in which, when the histogram is divided into two classes at a certain threshold, a threshold obtained when the variance between the classes is maximized is used as a binarization threshold, and a binarization method of setting the threshold for an image having a gradation in accordance with the local density.
In the binarization methods in the conventional image processing apparatus, however, the following problems arise.
More specifically, in the simple binarization method using the fixed threshold, a proper threshold is difficult to set between the object density and background density within an image. As a result, the entire image becomes excessively dark or bright. In the Otsu's method, when the distributions of two classes are greatly different from each other, the threshold shifts to a larger class, and a binary image with many noise components is undesirably generated. In the binarization method of setting the threshold in accordance with the local density, a block skew easily occurs because the image is divided into local regions. Even if an optimal threshold can be specified, gray scale information such as the background and characters of an original image is lost by binarization.